Discovering Plausible Explanations of Carcinogenecity in Chemical Compounds 1st Edition by Eva Armengol 9783540734987

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ISBN 13: 9783540734987

Author: Eva Armengol

The goal of predictive toxicology is the automatic construction of carcinogenecity models. Most common artificial intelligence techniques used to construct these models are inductive learning methods. In a previous work we presented an approach that uses lazy learning methods for solving the problem of predicting carcinogenecity. Lazy learning methods solve new problems based on their similarity to already solved problems. Nevertheless, a weakness of these kind of methods is that sometimes the result is not completely understandable by the user. In this paper we propose an explanation scheme for a concrete lazy learning method. This scheme is particularly interesting to justify the predictions about the carcinogenesis of chemical compounds.

Discovering Plausible Explanations of Carcinogenecity in Chemical Compounds 1st Table of contents:

1 Introduction

2 Representation of the chemical compounds using
feature terms

3 Lazy Induction of Descriptions

4 How results of a lazy learning method can be
explained?

5 The explanation scheme

6 Related Work

7 Conclusions and Future Work

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